scholarly journals Global Analysis of Cell Type-Specific Gene Expression

2003 ◽  
Vol 4 (2) ◽  
pp. 208-215 ◽  
Author(s):  
David W. Galbraith

The tissues and organs of multicellular eukaryotes are frequently observed to comprise complex three-dimensional interspersions of different cell types. It is a reasonable assumption that different global patterns of gene expression are found within these different cell types. This review outlines general experimental strategies designed to characterize these global gene expression patterns, based on a combination of methods of transgenic fluorescent protein (FP) expression and targeting, of flow cytometry and sorting and of high-throughput gene expression analysis.

2021 ◽  
pp. 002203452110120
Author(s):  
C. Gluck ◽  
S. Min ◽  
A. Oyelakin ◽  
M. Che ◽  
E. Horeth ◽  
...  

The parotid, submandibular, and sublingual glands represent a trio of oral secretory glands whose primary function is to produce saliva, facilitate digestion of food, provide protection against microbes, and maintain oral health. While recent studies have begun to shed light on the global gene expression patterns and profiles of salivary glands, particularly those of mice, relatively little is known about the location and identity of transcriptional control elements. Here we have established the epigenomic landscape of the mouse submandibular salivary gland (SMG) by performing chromatin immunoprecipitation sequencing experiments for 4 key histone marks. Our analysis of the comprehensive SMG data sets and comparisons with those from other adult organs have identified critical enhancers and super-enhancers of the mouse SMG. By further integrating these findings with complementary RNA-sequencing based gene expression data, we have unearthed a number of molecular regulators such as members of the Fox family of transcription factors that are enriched and likely to be functionally relevant for SMG biology. Overall, our studies provide a powerful atlas of cis-regulatory elements that can be leveraged for better understanding the transcriptional control mechanisms of the mouse SMG, discovery of novel genetic switches, and modulating tissue-specific gene expression in a targeted fashion.


2019 ◽  
Author(s):  
Tom Aharon Hait ◽  
Ran Elkon ◽  
Ron Shamir

AbstractSpatiotemporal gene expression patterns are governed to a large extent by enhancer elements, typically located distally from their target genes. Identification of enhancer-promoter (EP) links that are specific and functional in individual cell types is a key challenge in understanding gene regulation. We introduce CT-FOCS, a new statistical inference method that utilizes multiple replicates per cell type to infer cell type-specific EP links. Computationally predicted EP links are usually benchmarked against experimentally determined chromatin interactions measured by ChIA-PET and promoter-capture HiC techniques. We expand this validation scheme by using also loops that overlap in their anchor sites. In analyzing 1,366 samples from ENCODE, Roadmap epigenomics and FANTOM5, CT-FOCS inferred highly cell type-specific EP links more accurately than state-of-the-art methods. We illustrate how our inferred EP links drive cell type-specific gene expression and regulation.


PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244864
Author(s):  
Carlos Mora-Martinez

Large amounts of effort have been invested in trying to understand how a single genome is able to specify the identity of hundreds of cell types. Inspired by some aspects of Caenorhabditis elegans biology, we implemented an in silico evolutionary strategy to produce gene regulatory networks (GRNs) that drive cell-specific gene expression patterns, mimicking the process of terminal cell differentiation. Dynamics of the gene regulatory networks are governed by a thermodynamic model of gene expression, which uses DNA sequences and transcription factor degenerate position weight matrixes as input. In a version of the model, we included chromatin accessibility. Experimentally, it has been determined that cell-specific and broadly expressed genes are regulated differently. In our in silico evolved GRNs, broadly expressed genes are regulated very redundantly and the architecture of their cis-regulatory modules is different, in accordance to what has been found in C. elegans and also in other systems. Finally, we found differences in topological positions in GRNs between these two classes of genes, which help to explain why broadly expressed genes are so resilient to mutations. Overall, our results offer an explanatory hypothesis on why broadly expressed genes are regulated so redundantly compared to cell-specific genes, which can be extrapolated to phenomena such as ChIP-seq HOT regions.


2013 ◽  
Vol 24 (3) ◽  
pp. 246-260 ◽  
Author(s):  
Patricia L. Carlisle ◽  
David Kadosh

Candida albicans, the most common cause of human fungal infections, undergoes a reversible morphological transition from yeast to pseudohyphal and hyphal filaments, which is required for virulence. For many years, the relationship among global gene expression patterns associated with determination of specific C. albicans morphologies has remained obscure. Using a strain that can be genetically manipulated to sequentially transition from yeast to pseudohyphae to hyphae in the absence of complex environmental cues and upstream signaling pathways, we demonstrate by whole-genome transcriptional profiling that genes associated with pseudohyphae represent a subset of those associated with hyphae and are generally expressed at lower levels. Our results also strongly suggest that in addition to dosage, extended duration of filament-specific gene expression is sufficient to drive the C. albicans yeast-pseudohyphal-hyphal transition. Finally, we describe the first transcriptional profile of the C. albicans reverse hyphal-pseudohyphal-yeast transition and demonstrate that this transition involves not only down-regulation of known hyphal-specific, genes but also differential expression of additional genes that have not previously been associated with the forward transition, including many involved in protein synthesis. These findings provide new insight into genome-wide expression patterns important for determining fungal morphology and suggest that in addition to similarities, there are also fundamental differences in global gene expression as pathogenic filamentous fungi undergo forward and reverse morphological transitions.


Development ◽  
1999 ◽  
Vol 126 (13) ◽  
pp. 2883-2890 ◽  
Author(s):  
C. Tilmann ◽  
B. Capel

In mammals a single gene on the Y chromosome, Sry, controls testis formation. One of the earliest effects of Sry expression is the induction of somatic cell migration from the mesonephros into the XY gonad. Here we show that mesonephric cells are required for cord formation and male-specific gene expression in XY gonads in a stage-specific manner. Culturing XX gonads with an XY gonad at their surface, as a ‘sandwich’, resulted in cell migration into the XX tissue. Analysis of sandwich gonads revealed that in the presence of migrating cells, XX gonads organized cord structures and acquired male-specific gene expression patterns. From these results, we conclude that mesonephric cell migration plays a critical role in the formation of testis cords and the differentiation of XY versus XX cell types.


2017 ◽  
Author(s):  
Garth R. Ilsley ◽  
Ritsuko Suyama ◽  
Takeshi Noda ◽  
Nori Satoh ◽  
Nicholas M. Luscombe

AbstractSingle-cell RNA-seq has been established as a reliable and accessible technique enabling new types of analyses, such as identifying cell types and studying spatial and temporal gene expression variation and change at single-cell resolution. Recently, single-cell RNA-seq has been applied to developing embryos, which offers great potential for finding and characterising genes controlling the course of development along with their expression patterns. In this study, we applied single-cell RNA-seq to the 16-cell stage of the Ciona embryo, a marine chordate and performed a computational search for cell-specific gene expression patterns. We recovered many known expression patterns from our single-cell RNA-seq data and despite extensive previous screens, we succeeded in finding new cell-specific patterns, which we validated by in situ and single-cell qPCR.


2018 ◽  
Author(s):  
Michael L. Mucenski ◽  
Robert Mahoney ◽  
Mike Adam ◽  
Andrew S. Potter ◽  
S. Steven Potter

AbstractThe uterus is a remarkable organ that must guard against infections while maintaining the ability to support growth of a fetus without rejection. The Hoxa10 and Hoxa11 genes have previously been shown to play essential roles in uterus development and function. In this report we show that the Hoxc9,10,11 genes play a redundant role in the formation of uterine glands. In addition, we use single cell RNA-seq to create a high resolution gene expression atlas of the developing wild type mouse uterus. Cell types and subtypes are defined, for example dividing endothelial cells into arterial, venous, capillary, and lymphatic, while epithelial cells separate into luminal and glandular subtypes. Further, a surprising heterogeneity of stromal and myocyte cell types are identified. Transcription factor codes and ligand/receptor interactions are characterized. We also used single cell RNA-seq to globally define the altered gene expression patterns in all developing uterus cell types for two Hox mutants, with 8 or 9 mutant Hox genes. The mutants show a striking disruption of Wnt signaling as well as the Cxcl12/Cxcr4 ligand/receptor axis.Summary statementA single cell RNA-seq study of the developing mouse uterus defines cellular heterogeneities, lineage specific gene expression programs and perturbed pathways in Hox9,10,11 mutants.


2019 ◽  
Author(s):  
David J. Forsthoefel ◽  
Nicholas I. Cejda ◽  
Umair W. Khan ◽  
Phillip A. Newmark

AbstractOrgan regeneration requires precise coordination of new cell differentiation and remodeling of uninjured tissue to faithfully re-establish organ morphology and function. An atlas of gene expression and cell types in the uninjured state is therefore an essential pre-requisite for understanding how damage is repaired. Here, we use laser-capture microdissection (LCM) and RNA-Seq to define the transcriptome of the intestine of Schmidtea mediterranea, a planarian flatworm with exceptional regenerative capacity. Bioinformatic analysis of 1,844 intestine-enriched transcripts suggests extensive conservation of digestive physiology with other animals, including humans. Comparison of the intestinal transcriptome to purified absorptive intestinal cell (phagocyte) and published single-cell expression profiles confirms the identities of known intestinal cell types, and also identifies hundreds of additional transcripts with previously undetected intestinal enrichment. Furthermore, by assessing the expression patterns of 143 transcripts in situ, we discover unappreciated mediolateral regionalization of gene expression and cell-type diversity, especially among goblet cells. Demonstrating the utility of the intestinal transcriptome, we identify 22 intestine-enriched transcription factors, and find that several have distinct functional roles in the regeneration and maintenance of goblet cells. Furthermore, depletion of goblet cells inhibits planarian feeding and reduces viability. Altogether, our results show that LCM is a viable approach for assessing tissue-specific gene expression in planarians, and provide a new resource for further investigation of digestive tract regeneration, the physiological roles of intestinal cell types, and axial polarity.


Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 3840-3840
Author(s):  
Carsten Poggel ◽  
Timo Adams ◽  
Sabine Martin ◽  
Carola Pickel ◽  
Nicole Prahl ◽  
...  

Abstract Microarray-based gene expression profiling has been used to develop clinically relevant molecular classifiers for many different diseases. Furthermore, it has been shown for various chronic diseases that specific gene expression patterns are reflected at the level of blood cells. However, blood is a complex tissue comprising numerous cell types. Therefore, the contribution of rare cell types to a whole blood expression profile might not be detected and a substantial proportion of what is usually reported as “up-regulation” or “down-regulation” might actually be the result of a shift in cell populations and not of a true regulatory process. In order to circumvent these problems, several techniques have been established to analyze purified subpopulations rather than whole blood samples. Previously, it has been shown, for example, that reproducible gene expression profiles can be generated by positive selection of blood cell subsets from PBMCs1. As the preparation of PBMCs by, for example, Ficoll is time-consuming, inconvenient, and not amenable to automation, we have set up a combined direct whole blood cell separation and gene expression profiling protocol. By using Whole Blood CD14 MicroBeads in combination with the autoMACS Pro™ Separator, the separation protocol generally allowed enrichment of monocytes from whole blood within 30 min with purities higher than 90%. In combination with the depletion of neutrophils, the major source of contaminating RNA, purities increased to over 95% for all tested blood donors. Monocytes included the CD14bright/CD16− as well as the CD14dim/CD16+ populations. To assess the reproducibility of gene expression profiles and the influence of several experimental parameters, monocytes were sorted from 5 ml whole blood. RNA was extracted and hybridized to microarrays and the Pearson correlation coefficients of pairwise comparisons were calculated. Technical repeats of monocyte analysis from blood donated at different days showed a higher correlation coefficient than whole blood RNA. Blood storage at room temperature resulted in a strong deregulation of many genes, whereas blood stored at 4°C showed minimal changes, which is in agreement with previous studies. Skipping the centrifugation step, which is used to remove unbound MicroBeads did not alter the gene expression profiles. Incubation of sorted cells in PrepProtect™ Stabilization Buffer showed no alteration of gene expression thus enabling the shipping of cells without liquid nitrogen. Monocytes play a crucial role in diseases like atherosclerosis. Our rapid and simple protocol for combined direct cell sorting from whole blood and gene expression profiling of monocytes might help to ease the discovery of new biomarkers and to screen and monitor patients. 1 Lyons et al., BMC Genomics (2007), 8:64.


2020 ◽  
Author(s):  
Shunfu Mao ◽  
Yue Zhang ◽  
Georg Seelig ◽  
Sreeram Kannan

AbstractSingle-cell RNA sequencing (scRNA-seq) is widely used for analyzing gene expression in multi-cellular systems and provides unprecedented access to cellular heterogeneity. scRNA-seq experiments aim to identify and quantify all cell types present in a sample. Measured single-cell transcriptomes are grouped by similarity and the resulting clusters are mapped to cell types based on cluster-specific gene expression patterns. While the process of generating clusters has become largely automated, annotation remains a laborious ad-hoc effort that requires expert biological knowledge. Here, we introduce CellMeSH - a new automated approach to identifying cell types based on prior literature. CellMeSH combines a database of gene-cell type associations with a probabilistic method for database querying. The database is constructed by automatically linking gene and cell type information from millions of publications using existing indexed literature resources. Compared to manually constructed databases, CellMeSH is more comprehensive and scales automatically. The probabilistic query method enables reliable information retrieval even though the gene-cell type associations extracted from the literature are necessarily noisy. CellMeSH achieves up to 60% top-1 accuracy and 90% top-3 accuracy in annotating the cell types on a human dataset, and up to 58.8% top-1 accuracy and 88.2% top-3 accuracy on three mouse datasets, which is consistently better than existing approaches.AvailabilityWeb server: https://uncurl.cs.washington.edu/db_query and API: https://github.com/shunfumao/cellmesh


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